title: On the follow-up of genome-wide association studies: an overall test for the most promising SNPs.
abstract: Even in large-scale genome-wide association studies (GWASs), only a fraction of the true associations are detected at the genome-wide significance level. When few or no associations reach the significance threshold, one strategy is to follow up on the most promising candidates, i.e. the single nucleotide polymorphisms (SNPs) with the smallest association-test P-values, by genotyping them in additional studies. In this communication, we propose an overall test for GWASs that analyzes the SNPs with the most promising P-values simultaneously and therefore allows an early assessment of whether the follow-up of the selected SNPs is likely promising. We theoretically derive the properties of the proposed overall test under the null hypothesis and assess its power based on simulation studies. An application to a GWAS for chronic obstructive pulmonary disease suggests that there are true association signals among the top SNPs and that an additional follow-up study is promising.
authors.affiliation: Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. pjlipman@fas.harvard.edu
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Lipman
authors.forename: Michael H
authors.initials: MH
authors.lastname: Cho
authors.forename: Per
authors.initials: P
authors.lastname: Bakke
authors.forename: Amund
authors.initials: A
authors.lastname: Gulsvik
authors.forename: Xiangyang
authors.initials: X
authors.lastname: Kong
authors.forename: David A
authors.initials: DA
authors.lastname: Lomas
authors.forename: Wayne
authors.initials: W
authors.lastname: Anderson
authors.forename: Edwin K
authors.initials: EK
authors.lastname: Silverman
authors.forename: Christoph
authors.initials: C
authors.lastname: Lange
mesh_terms: D003198:Computer Simulation; D055106:Genome-Wide Association Study / Q000706:statistics & numerical data*; D006801:Humans; D015810:Linkage Disequilibrium; D008957:Models, Genetic; D015233:Models, Statistical; D017720:Molecular Epidemiology; D020641:Polymorphism, Single Nucleotide; D029424:Pulmonary Disease, Chronic Obstructive / Q000453:epidemiology / Q000235:genetics